Merge branch 'Theano_updated' into github.SurfaceNet

README.md

@@ -8,6 +8,10 @@ The [poster pdf](https://www.researchgate.net/publication/321126305_ICCV2017_Sur
 
 1. install [Nvidia driver 375 + cuda 8.0 + cudnn v5.1](https://github.com/mjiUST/driver_cuda_cudnn)
 2. install the conda environment by: `bash installEnv.sh`
+    * DON'T WORRY, conda will generate an isolated environment for SurfaceNet with python2.7, anaconda, theano, ... etc. That means all your libraries / packeges' version will not be affacted, at the same time the `~/.bashrc` file will not be changed.
+    * before you run, PLEASE change the CUDA/CUDNN path in the files: 
+        - `./config/activate-cuda.sh` change the 1st line to your cuda path, e.g.: `export CUDA_ROOT=/usr/local/cuda`
+        - `./config/activate-cudnn.sh` change the 1st line to your cudnn path, e.g.: `export CUDNN_ROOT=/home/<your-user-name>/libs/cudnn`
 3. download the network model to the folder "./inputs/SurfaceNet_models" from the Dropbox [folder](https://www.dropbox.com/sh/8xs0u57ikj4qfvr/AADRQFQyJfG3WfH7ZvpcWmMKa?dl=0)
 4. if the conda environment has been installed, one can activate it by: `. activate SurfaceNet`; deactivate it by: `. deactivate`.
 5. in terminal run: `python main.py` 

config/activate-cuda.sh

@@ -0,0 +1,7 @@
+export CUDA_ROOT=/usr/local/cuda   #  set conda-env specific cuda path
+export LD_LIBRARY_PATH_CUDA_BACKUP="$LD_LIBRARY_PATH"
+export LD_LIBRARY_PATH=$CUDA_ROOT/lib64:$LD_LIBRARY_PATH
+export CPATH_CUDA_BACKUP="$CPATH"
+export CPATH=$CUDA_ROOT/include:$CPATH
+export LIBRARY_PATH_CUDA_BACKUP="$LIBRARY_PATH"
+export LIBRARY_PATH=$CUDA_ROOT/lib64:$LIBRARY_PATH

config/activate-cudnn.sh

@@ -0,0 +1,7 @@
+export CUDNN_ROOT=/usr/local/cuda   #  set conda-env specific cudnn path, e.g.: /home/<your-user-name>/libs/cudnn 
+export LD_LIBRARY_PATH_CUDNN_BACKUP="$LD_LIBRARY_PATH"
+export LD_LIBRARY_PATH=$CUDNN_ROOT/lib64:$LD_LIBRARY_PATH
+export CPATH_CUDNN_BACKUP="$CPATH"
+export CPATH=$CUDNN_ROOT/include:$CPATH
+export LIBRARY_PATH_CUDNN_BACKUP="$LIBRARY_PATH"
+export LIBRARY_PATH=$CUDNN_ROOT/lib64:$LIBRARY_PATH

config/deactivate-cuda.sh

@@ -0,0 +1,6 @@
+export LD_LIBRARY_PATH="$LD_LIBRARY_PATH_PYGPU_CUDA_BACKUP"
+unset LD_LIBRARY_PATH_PYGPU_CUDA_BACKUP
+export CPATH="$CPATH_CUDA_BACKUP"
+unset CPATH_CUDA_BACKUP
+export LIBRARY_PATH="$LIBRARY_PATH_CUDA_BACKUP"
+unset LIBRARY_PATH_CUDA_BACKUP

config/deactivate-cudnn.sh

@@ -0,0 +1,6 @@
+export LD_LIBRARY_PATH="$LD_LIBRARY_PATH_PYGPU_CUDNN_BACKUP"
+unset LD_LIBRARY_PATH_PYGPU_CUDNN_BACKUP
+export CPATH="$CPATH_CUDNN_BACKUP"
+unset CPATH_CUDNN_BACKUP
+export LIBRARY_PATH="$LIBRARY_PATH_CUDNN_BACKUP"
+unset LIBRARY_PATH_CUDNN_BACKUP

installEnv.sh

@@ -1,7 +1,6 @@
 #!/bin/bash -evx
 
 conda_env_name=SurfaceNet
-cuda_root=/usr/local/cuda
 
 # set -e # To exit the script as soon as one of the commands failed
 cd ~/Downloads
@@ -16,29 +15,29 @@ else
     . ~/.bashrc    # to enable the conda command
 fi
 
-# config .bashrc, can change the CUDA_ROOT path
-echo 'export CUDA_ROOT=$cuda_root' >> ~/.bashrc
-echo 'export LD_LIBRARY_PATH=$CUDA_ROOT/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc
-echo 'export CPATH=$CUDA_ROOT/include:$CPATH' >> ~/.bashrc
-echo 'export LIBRARY_PATH=$CUDA_ROOT/lib64:$LIBRARY_PATH' >> ~/.bashrc
-. ~/.bashrc    # source before `source activate conda_env`
+cd -  # cd back to SurfaceNet work dir
 
 # create new environment
 if conda info --env | grep -w "$conda_env_name" >/dev/null; then
     echo "The '$conda_env_name' conda env exists."    # but the env will be visible even thoug the installation was terminated. In this case you should delete this conda env first.
 else    # if the env does not exist.
-    conda create -n $conda_env_name python=2.7 anaconda    # install anaconda with the majority of the depandencies, (very large)
+    conda create -n $conda_env_name python=2.7 anaconda --yes    # install anaconda with the majority of the depandencies, (very large)
 fi
+# assume the miniconda path is ~/miniconda2/
+mkdir -p ~/miniconda2/envs/$conda_env_name/etc/conda/activate.d/
+cp ./config/act* ~/miniconda2/envs/$conda_env_name/etc/conda/activate.d/   # before copy *PLEASE* change the CUDA/CUDNN path in the first line of these files accordingly
+mkdir -p ~/miniconda2/envs/$conda_env_name/etc/conda/deactivate.d/
+cp ./config/de* ~/miniconda2/envs/$conda_env_name/etc/conda/deactivate.d/
 . activate $conda_env_name      # seperate environment. Can use command `which python` to check the path of the local python/packeges
 
 # install packeges
-conda install theano pygpu --yes    # http://www.deeplearning.net/software/theano/install_ubuntu.html#requirements-installation-through-conda-recommended
+conda install -c rdonnelly theano -y  # 0.9.0 version theano
 pip install --upgrade https://github.com/Lasagne/Lasagne/archive/master.zip    # http://lasagne.readthedocs.io/en/latest/user/installation.html#bleeding-edge-version
 pip install plyfile progressbar
 
 # config .theanorc,
-if ls ~/.theanorc >/dev/null; then cp ~/.theanorc ~/.theanorc_backup; echo ".theanorc_backup was backed up"; fi
-echo -e "[global] \nfloatX=float32 \ndevice=cuda \noptimizer=fast_run \n \nallow_gc=True \ngpuarray.preallocate=-1 \n \nnvcc.fastmath=True \n \n[cuda] \nroot=/usr/local/cuda" > ~/.theanorc
+if ls ~/.theanorc >/dev/null; then cp ~/.theanorc ~/.theanorc_SurfaceNet_backup; echo ".theanorc_SurfaceNet_backup was backed up"; fi
+echo -e "[global] \nfloatX=float32 \ndevice=cuda \noptimizer=fast_run \n \nallow_gc=True \ngpuarray.preallocate=-1 \n \nnvcc.fastmath=True \n" > ~/.theanorc
 
 # test lasagne:
 echo "Try to import lasagne. If there is no error, congratulations!"